System-Theoretic Principles and Decentralized Sensor Network and Control Algorithms for Dynamic Data-Driven

Abstract

Situational awareness and response technologies using interconnected static and mobile sensorshave the capability to enhance combat power and to contribute to the success of noncombatmilitary operations. With this one-year seed funding, this project will establish the fundamentalbasis of a novel integrated multiagent estimation and control framework for enabling correct,reliable, and communication-efficient dynamic data-driven situational awareness and responseapplications through two synergistic research tasks: A) Develop a decentralized informationfusion framework for situational awareness in the presence of heterogeneity resulting from thesensing capabilities of nodes and nonidentical sensor types with complementary propertiesdistributed over the network. B) Integrate the decentralized information fusion framework withcommunication-efficient multiagent navigation and adaptive optimal control approach. Thefundamental basis of a novel integrated multiagent estimation and control framework to beestablished through this one-year seed funding will significantly advance the state-of-the-art indecentralized estimation, intelligent control, wireless sensor networks, and networked multiagentsystems and provide insights on how to design, implement, and maintain high-confidence andhigh-performance dynamic data driven multiagent estimation and control systems. Our resultscan impact a broad range of Department of Defense situational awareness and response missionsinvolving but not limited to battlefield surveillance, target tracking, search and rescue missions,nuclear, biological, and chemical attack detection, and monitoring enemy forces.

Document Details

Document Type
DoD Grant Award
Publication Date
Sep 11, 2017
Source ID
FA95501710303

Entities

People

  • Tansel Yucelen

Organizations

  • Air Force Office of Scientific Research
  • United States Air Force
  • University of South Florida

Tags

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • Agent-Based Social Robotics and Mobile-Assisted Learning in Virtual Environments.
  • Distributed Systems and Data Platform Development